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Can the NVIDIA RTX 5070 run GLM-5 744B-A40B?

RTX 5070 × GLM-5 744B-A40B8K context
NoDoes not fit in memory
Memory at Q4_K_M452.4 GB of 12 GB
Weights 451.1 GBKV cache 0.7 GBRuntime 0.6 GB
  1. FP16
  2. Q8_0
  3. Q6_K
  4. Q5_K_M
  5. Q4_K_M
  6. Q3_K_M
  7. Q2_K

No. Even at Q4_K_M, GLM-5 744B-A40B needs about 452.4 GB, but the NVIDIA RTX 5070 has 12 GB usable. You could offload some layers to system RAM, but it will be very slow.

Try other context lengths

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Memory needed by quantization

At 8,192 tokens of context. The black line marks the 12 GB the NVIDIA RTX 5070 can use.

QuantQualityMemoryFits?Speed
FP16Full quality1489.3 GBToo big—
Q8_0Near-lossless791.8 GBToo big—
Q6_KExcellent611.4 GBToo big—
Q5_K_MVery good530.5 GBToo big—
Q4_K_MGood, most popular452.4 GBToo big—
Q3_K_MNoticeably degraded365 GBToo big—
Q2_KHeavily degraded280.3 GBToo big—

Measured speed from real RTX 5070 owners

Tokens per second that people measured on their own NVIDIA RTX 5070, next to our estimate.

No one has measured GLM-5 744B-A40B on the NVIDIA RTX 5070 yet. The speeds above are estimates. Run the benchmark and yours becomes the first real number on this page.

Have an RTX 5070? Add your real speed

One command times GLM-5 744B-A40B in your own Ollama, shows you exactly what it would send, and asks before sending anything. No sign-up, no personal data.

macOS and Linux

curl -fsSL https://gpufit.dev/bench.sh | sh

Windows (PowerShell)

irm https://gpufit.dev/bench.ps1 | iex

How the benchmark works

Models that run well on the NVIDIA RTX 5070

Frequently asked questions

Can NVIDIA RTX 5070 run GLM-5 744B-A40B?

No. Even at Q4_K_M, GLM-5 744B-A40B needs about 452.4 GB, but the NVIDIA RTX 5070 has 12 GB usable. You could offload some layers to system RAM, but it will be very slow.

How much VRAM does GLM-5 744B-A40B need?

About 452.4 GB at Q4_K_M with 8,192 tokens of context, and about 1489.3 GB at full FP16 precision.

How fast is GLM-5 744B-A40B on the NVIDIA RTX 5070?

It does not fit in the NVIDIA RTX 5070's memory, so most layers would run from system RAM and generation would be very slow.